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Abstract: We participated in three of the protein-protein interaction subtasks of the Second BioCreative Challenge: classification of abstracts relevant for protein-protein interaction (IAS), discovery of protein pairs (IPS) and text passages characterizing protein interaction (ISS) in full text documents. We approache... |
Title: A note on the separability index |
Abstract: In discriminating between objects from different classes, the more separable these classes are the less computationally expensive and complex a classifier can be used. One thus seeks a measure that can quickly capture this separability concept between classes whilst having an intuitive interpretation on what ... |
Title: An analysis of a random algorithm for estimating all the matchings |
Abstract: Counting the number of all the matchings on a bipartite graph has been transformed into calculating the permanent of a matrix obtained from the extended bipartite graph by Yan Huo, and Rasmussen presents a simple approach (RM) to approximate the permanent, which just yields a critical ratio O($n\omega(n)$) fo... |
Title: Emerge-Sort: Converging to Ordered Sequences by Simple Local Operators |
Abstract: In this paper we examine sorting on the assumption that we do not know in advance which way to sort a sequence of numbers and we set at work simple local comparison and swap operators whose repeating application ends up in sorted sequences. These are the basic elements of Emerge-Sort, our approach to self-org... |
Title: A novel changepoint detection algorithm |
Abstract: We propose an algorithm for simultaneously detecting and locating changepoints in a time series, and a framework for predicting the distribution of the next point in the series. The kernel of the algorithm is a system of equations that computes, for each index i, the probability that the last (most recent) ch... |
Title: Decomposition Principles and Online Learning in Cross-Layer Optimization for Delay-Sensitive Applications |
Abstract: In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sensitive applications and the underlying time-varying network conditions. We consider both the independently decodable data units (DU... |
Title: Obtaining Depth Maps From Color Images By Region Based Stereo Matching Algorithms |
Abstract: In the paper, region based stereo matching algorithms are developed for extraction depth information from two color stereo image pair. A filter eliminating unreliable disparity estimation was used for increasing reliability of the disparity map. Obtained results by algorithms were represented and compared. |
Title: A Novel Clustering Algorithm Based on Quantum Random Walk |
Abstract: The enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum random walk (QRW) with the problem of data clustering, and develop two clustering algorithms based on the one dimensional QRW. Then, the probability distributions on the positions induced ... |
Title: Optimal sequential testing of two simple hypotheses in presence of control variables |
Abstract: Suppose that at any stage of a statistical experiment a control variable $X$ that affects the distribution of the observed data $Y$ can be used. The distribution of $Y$ depends on some unknown parameter $\theta$, and we consider the classical problem of testing a simple hypothesis $H_0: \theta=\theta_0$ again... |
Title: Logic programs with propositional connectives and aggregates |
Abstract: Answer set programming (ASP) is a logic programming paradigm that can be used to solve complex combinatorial search problems. Aggregates are an ASP construct that plays an important role in many applications. Defining a satisfactory semantics of aggregates turned out to be a difficult problem, and in this pap... |
Title: Parallel hierarchical sampling: a practical multiple-chains sampler for Bayesian model selection |
Abstract: This paper introduces the parallel hierarchical sampler (PHS), a Markov chain Monte Carlo algorithm using several chains simultaneously. The connections between PHS and the parallel tempering (PT) algorithm are illustrated, convergence of PHS joint transition kernel is proved and and its practical advantages ... |
Title: Comparison of Data Imputation Techniques and their Impact |
Abstract: Missing and incomplete information in surveys or databases can be imputed using different statistical and soft-computing techniques. This paper comprehensively compares auto-associative neural networks (NN), neuro-fuzzy (NF) systems and the hybrid combinations the above methods with hot-deck imputation. The t... |
Title: Multi-Agent Reinforcement Learning and Genetic Policy Sharing |
Abstract: The effects of policy sharing between agents in a multi-agent dynamical system has not been studied extensively. I simulate a system of agents optimizing the same task using reinforcement learning, to study the effects of different population densities and policy sharing. I demonstrate that sharing policies d... |
Title: Missing Data using Decision Forest and Computational Intelligence |
Abstract: Autoencoder neural network is implemented to estimate the missing data. Genetic algorithm is implemented for network optimization and estimating the missing data. Missing data is treated as Missing At Random mechanism by implementing maximum likelihood algorithm. The network performance is determined by calcu... |
Title: Simultaneous confidence intervals for the population cell means, for two-by-two factorial data, that utilize uncertain prior information |
Abstract: Consider a two-by-two factorial experiment with more than 1 replicate. Suppose that we have uncertain prior information that the two-factor interaction is zero. We describe new simultaneous frequentist confidence intervals for the 4 population cell means, with simultaneous confidence coefficient 1-alpha, that... |
Title: Estimating limits from Poisson counting data using Dempster--Shafer analysis |
Abstract: We present a Dempster--Shafer (DS) approach to estimating limits from Poisson counting data with nuisance parameters. Dempster--Shafer is a statistical framework that generalizes Bayesian statistics. DS calculus augments traditional probability by allowing mass to be distributed over power sets of the event s... |
Title: Identification of parameters underlying emotions and a classification of emotions |
Abstract: The standard classification of emotions involves categorizing the expression of emotions. In this paper, parameters underlying some emotions are identified and a new classification based on these parameters is suggested. |
Title: Convex Sparse Matrix Factorizations |
Abstract: We present a convex formulation of dictionary learning for sparse signal decomposition. Convexity is obtained by replacing the usual explicit upper bound on the dictionary size by a convex rank-reducing term similar to the trace norm. In particular, our formulation introduces an explicit trade-off between siz... |
Title: Trek separation for Gaussian graphical models |
Abstract: Gaussian graphical models are semi-algebraic subsets of the cone of positive definite covariance matrices. Submatrices with low rank correspond to generalizations of conditional independence constraints on collections of random variables. We give a precise graph-theoretic characterization of when submatrices ... |
Title: Prediction with Restricted Resources and Finite Automata |
Abstract: We obtain an index of the complexity of a random sequence by allowing the role of the measure in classical probability theory to be played by a function we call the generating mechanism. Typically, this generating mechanism will be a finite automata. We generate a set of biased sequences by applying a finite ... |
Title: An Ensemble Kalman-Particle Predictor-Corrector Filter for Non-Gaussian Data Assimilation |
Abstract: An Ensemble Kalman Filter (EnKF, the predictor) is used make a large change in the state, followed by a Particle Filer (PF, the corrector) which assigns importance weights to describe non-Gaussian distribution. The weights are obtained by nonparametric density estimation. It is demonstrated on several numeric... |
Title: Characterizing Truthful Multi-Armed Bandit Mechanisms |
Abstract: We consider a multi-round auction setting motivated by pay-per-click auctions for Internet advertising. In each round the auctioneer selects an advertiser and shows her ad, which is then either clicked or not. An advertiser derives value from clicks; the value of a click is her private information. Initially,... |
Title: Classification of Cell Images Using MPEG-7-influenced Descriptors and Support Vector Machines in Cell Morphology |
Abstract: Counting and classifying blood cells is an important diagnostic tool in medicine. Support Vector Machines are increasingly popular and efficient and could replace artificial neural network systems. Here a method to classify blood cells is proposed using SVM. A set of statistics on images are implemented in C+... |
Title: Urologic robots and future directions |
Abstract: PURPOSE OF REVIEW: Robot-assisted laparoscopic surgery in urology has gained immense popularity with the daVinci system, but a lot of research teams are working on new robots. The purpose of this study is to review current urologic robots and present future development directions. RECENT FINDINGS: Future syst... |
Title: Physics of risk and uncertainty in quantum decision making |
Abstract: The Quantum Decision Theory, developed recently by the authors, is applied to clarify the role of risk and uncertainty in decision making and in particular in relation to the phenomenon of dynamic inconsistency. By formulating this notion in precise mathematical terms, we distinguish three types of inconsiste... |
Title: A New Trend in Optimization on Multi Overcomplete Dictionary toward Inpainting |
Abstract: Recently, great attention was intended toward overcomplete dictionaries and the sparse representations they can provide. In a wide variety of signal processing problems, sparsity serves a crucial property leading to high performance. Inpainting, the process of reconstructing lost or deteriorated parts of imag... |
Title: Probabilistic SVM/GMM Classifier for Speaker-Independent Vowel Recognition in Continues Speech |
Abstract: In this paper, we discuss the issues in automatic recognition of vowels in Persian language. The present work focuses on new statistical method of recognition of vowels as a basic unit of syllables. First we describe a vowel detection system then briefly discuss how the detected vowels can feed to recognition... |
Title: Evaluating the Impact of Missing Data Imputation through the use of the Random Forest Algorithm |
Abstract: This paper presents an impact assessment for the imputation of missing data. The data set used is HIV Seroprevalence data from an antenatal clinic study survey performed in 2001. Data imputation is performed through five methods: Random Forests, Autoassociative Neural Networks with Genetic Algorithms, Autoass... |
Title: Pattern Recognition and Memory Mapping using Mirroring Neural Networks |
Abstract: In this paper, we present a new kind of learning implementation to recognize the patterns using the concept of Mirroring Neural Network (MNN) which can extract information from distinct sensory input patterns and perform pattern recognition tasks. It is also capable of being used as an advanced associative me... |
Title: Feature Selection By KDDA For SVM-Based MultiView Face Recognition |
Abstract: Applications such as face recognition that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced discriminatory power and a proper classifier, able to classify those complex features. Most of traditional Linear Discriminant Analysis s... |
Title: Face Detection Using Adaboosted SVM-Based Component Classifier |
Abstract: Recently, Adaboost has been widely used to improve the accuracy of any given learning algorithm. In this paper we focus on designing an algorithm to employ combination of Adaboost with Support Vector Machine as weak component classifiers to be used in Face Detection Task. To obtain a set of effective SVM-weak... |
Title: Nonparametric Estimation of Variance Function for Functional Data |
Abstract: This article investigates nonparametric estimation of variance functions for functional data when the mean function is unknown. We obtain asymptotic results for the kernel estimator based on squared residuals. Similar to the finite dimensional case, our asymptotic result shows the smoothness of the unknown me... |
Title: Standard Logics Are Valuation-Nonmonotonic |
Abstract: It has recently been discovered that both quantum and classical propositional logics can be modelled by classes of non-orthomodular and thus non-distributive lattices that properly contain standard orthomodular and Boolean classes, respectively. In this paper we prove that these logics are complete even for t... |
Title: Sequential multiple hypothesis testing in presence of control variables |
Abstract: Suppose that at any stage of a statistical experiment a control variable $X$ that affects the distribution of the observed data $Y$ at this stage can be used. The distribution of $Y$ depends on some unknown parameter $\theta$, and we consider the problem of testing multiple hypotheses $H_1: \theta=\theta_1$, ... |
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